Order sequence optimization for parts-to-picker intelligent robot system

Abstract

In this paper, we propose an order sorting model for the parts-to-picker intelligent robot system. By optimizing the sequence for order picking, the model increases the number of shared racks for orders within adjacent orders and picking stations, reduces the number of transportation times of the racks, thereby improving the efficiency of the warehouse system. Considering the order sequencing as the travelling salesman problem (TSP), we solve the order sorting model by the improved <italic>K</italic>-Means algorithm. Three sets of different batch orders are selected for simulation verification. After optimization, the transportation times of the system racks are reduced by 35.63% on average.